Instructions to use karths/binary_classification_train_infrastructure with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_infrastructure with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_infrastructure")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_infrastructure") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_infrastructure", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download metrics_visualisation.png from karths/binary_classification_train_infrastructure: direct link, hf CLI and curl.
- Browser
- Download file 25.3 kB
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https://huggingface.co/karths/binary_classification_train_infrastructure/resolve/main/metrics_visualisation.png
- Command line
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hf download hf://karths/binary_classification_train_infrastructure/metrics_visualisation.png
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curl -L -o metrics_visualisation.png https://huggingface.co/karths/binary_classification_train_infrastructure/resolve/main/metrics_visualisation.png
25.3 kB
